Saliency and Active Contour based Traffic Sign Detection
Year: 2012
Journal of Information and Computing Science, Vol. 7 (2012), Iss. 3 : pp. 235–240
Abstract
In this paper, we propose a new approach to detect salient traffic signs, which is based on visual saliency and auto-generated strokes for image segmentation. The proposed algorithm deals with two tasks on detecting traffic signs: auto-location and auto extraction. Firstly, inspired by recent work of visual saliency detection, we obtain the location of traffic signs in a natural image by multi-scale principle component analysis (MPCA). Secondly, in order to extract traffic signs, auto-generated strokes are used instead of drawing the strokes by the users, the sign board area is extracted using localizing Region-Based Active Contour. Extensive experiments on public datasets show that our approach outperforms state-of-the-art methods remarkably in salient traffic sign detection. Moreover, the proposed detection method has higher accurate rate and robustness to different natural scenes.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22647
Journal of Information and Computing Science, Vol. 7 (2012), Iss. 3 : pp. 235–240
Published online: 2012-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 6